At a Glance
- Tasks: Transform complex data into actionable insights that impact compensation decisions.
- Company: Join Elsevier, a global leader in information and analytics with an inclusive culture.
- Benefits: Flexible working hours, wellbeing initiatives, study assistance, and sabbaticals.
- Other info: Work in a dynamic environment with opportunities for personal and professional growth.
- Why this job: Make a real difference by improving data processes and automation in a supportive team.
- Qualifications: Experience with large datasets, advanced Excel skills, and knowledge of SQL or Python.
The predicted salary is between 35000 - 45000 £ per year.
This job is with Elsevier, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community.
Are you motivated by turning complex data into trusted, decision‑ready insights that directly impact how people are rewarded for their work? Do you enjoy improving data processes and automation to make systems more accurate, scalable, and reliable?
About our Team
Our team supports the accuracy and integrity of sales and compensation data across the organisation. We work closely with Sales Operations, Finance, and technology partners to ensure data is reliable, well controlled, and ready for critical reporting and payout cycles. The team focuses on continuous improvement, strengthening data quality, increasing automation, and reducing risk through clear processes, collaboration, and shared accountability.
About the Role
This role focuses on building, validating, and maintaining high‑quality participant‑level data that underpins sales compensation outcomes. You will work across sales, finance, and technology partners to ensure data is accurate, auditable, and ready for payout cycles. The role plays a key part in improving automation, reducing manual effort, and strengthening stakeholder confidence in compensation data.
Responsibilities
- Ingest and consolidate large datasets from Sales Operations, Finance, and CRM systems
- Map transactions and performance metrics to sales participants
- Own data quality controls, reconciliation processes, and audit trails
- Ensure accurate attribution of revenue, quotas, credits, overlays, and splits
- Prepare validated datasets to support compensation payout cycles
- Investigate and resolve data discrepancies and support audits
- Build reporting to track data accuracy, readiness, trends, and risks
- Review end‑to‑end processes to identify inefficiencies and implement automation and standardisation
Requirements
- Strong experience working with large, complex datasets
- Advanced Excel skills for analysis, reconciliation, and validation
- Experience in analytics, sales compensation, or related data operations
- Ability to perform root‑cause analysis and solve data quality issues
- Clear communication skills to work with technical and non‑technical stakeholders
- Experience preparing data for financial or compensation processes
- Knowledge of SQL or Python
- Familiarity with compensation platforms, CRM systems, and data visualisation tools
Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About the Business
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Data Analyst employer: Elsevier
At Elsevier, we pride ourselves on being an inclusive employer that values diversity and promotes a healthy work/life balance. Our supportive work culture encourages continuous improvement and collaboration, offering employees opportunities for growth through various wellbeing initiatives, flexible working hours, and professional development resources. Join us in making a meaningful impact on global health and research while enjoying the unique benefits tailored to your location.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Elsevier on LinkedIn. Ask them about their experiences and any tips they might have for landing the Data Analyst role. Personal connections can give you insights that job descriptions just can't.
✨Tip Number 2
Prepare for the interview by brushing up on your data skills. Make sure you're comfortable discussing your experience with large datasets, Excel, SQL, and Python. We want to see how you can turn complex data into actionable insights, so be ready to share examples!
✨Tip Number 3
Show off your problem-solving skills! Think of specific instances where you've tackled data quality issues or improved processes. We love candidates who can demonstrate their ability to enhance data accuracy and reliability.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Elsevier.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Analyst role. Highlight your experience with large datasets, Excel skills, and any relevant analytics work. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data and how you can contribute to our team. Be sure to mention your experience with automation and improving data processes.
Showcase Your Skills:Don’t forget to showcase your technical skills, especially in SQL or Python. If you've worked with compensation platforms or CRM systems, let us know! We love seeing candidates who can hit the ground running.
Apply Through Our Website:We encourage you to apply through our website for a smooth application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Good luck!
How to prepare for a job interview at Elsevier
✨Know Your Data Inside Out
Before the interview, dive deep into your past experiences with large datasets. Be ready to discuss specific examples where you improved data processes or resolved discrepancies. This will show your potential employer that you can handle the complexities of their data needs.
✨Brush Up on Your Technical Skills
Make sure you're comfortable with Excel, SQL, and Python. Practice common data analysis tasks and be prepared to demonstrate your skills during the interview. If they ask about automating processes, have a few ideas ready to share!
✨Communicate Clearly and Confidently
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex data concepts in simple terms. This will highlight your communication skills and show that you can bridge the gap between different teams.
✨Show Your Passion for Continuous Improvement
Be ready to discuss how you've identified inefficiencies in past roles and what steps you took to improve them. Employers love candidates who are proactive about enhancing processes and driving quality, so share your success stories!
